How to avoid predatory open access publishers

Adopting a safe publication strategy

Damien Belvèze

Université de Rennes

2023-07-11

Data management support for researchers
training sessions (data management, identifiers, reproducibility)
Data management plans
Data curation on ‘Recherche Data Gouv’ repository

1. predators and imposters

Elsevier has built up a war chest with $1.17 billion in net revenues, representing a 38% increase in sales. Researchers depend on these publishing compagnies for the quality assessment of their work. as a raw material, they yield for nothing the product of their public funded research, with which thoes compagnies will make extravagant profits by siphoning off university libraries’ finances. Or they will require research teams to pay 2 or 3 thousand dollars for so-called article processing charges in order to make their publication open access in their journals. In most of the cases, big publishing companies will make profit from both publication costs and subscriptions sold at a premium to libraries (> hybrid journals)

Elsevier, Springer, Mac Millan, Wiley, American Chemical abstracts are basically predators in the publishing market, but what we call usually predatory open access publishers are not those big companies, but smaller and newer companies who pretend to provide a consistent peer reviewing process but do nothing than take money from the authors.they are truly impostors, but they are called predators.

journal hijacking

figures

figure	source et crédits
Figure 1	Research Professional News

software used for this presentation

Most part of the software used for this presentation are open source “libre” software (thank you Richard M. Stallman)

Quarto 1.3.450
VScode 1.8.0
R :

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.3.0 (2023-04-21 ucrt)
 os       Windows 11 x64 (build 22631)
 system   x86_64, mingw32
 ui       RTerm
 language (EN)
 collate  French_France.utf8
 ctype    French_France.utf8
 tz       Europe/Paris
 date     2024-04-10
 pandoc   3.1.11 @ C:/PROGRA~1/Pandoc/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────
 package     * version date (UTC) lib source
 cli           3.6.2   2023-12-11 [1] CRAN (R 4.3.2)
 digest        0.6.34  2024-01-11 [1] CRAN (R 4.3.2)
 evaluate      0.23    2023-11-01 [1] CRAN (R 4.3.2)
 fastmap       1.1.1   2023-02-24 [1] CRAN (R 4.3.2)
 htmltools     0.5.7   2023-11-03 [1] CRAN (R 4.3.2)
 jsonlite      1.8.8   2023-12-04 [1] CRAN (R 4.3.2)
 knitr         1.45    2023-10-30 [1] CRAN (R 4.3.2)
 rlang         1.1.3   2024-01-10 [1] CRAN (R 4.3.2)
 rmarkdown     2.25    2023-09-18 [1] CRAN (R 4.3.0)
 rstudioapi    0.15.0  2023-07-07 [1] CRAN (R 4.3.2)
 sessioninfo   1.2.2   2021-12-06 [1] CRAN (R 4.3.2)
 xfun          0.42    2024-02-08 [1] CRAN (R 4.3.3)
 yaml          2.3.8   2023-12-11 [1] CRAN (R 4.3.2)

 [1] C:/Program Files/R/R-4.3.0/library

──────────────────────────────────────────────────────────────────────────────

l’éditeur de texte est VScode. VScode rend l’utilisation de Quarto plus facile (Quarto est un logiciel dépourvu d’interface graphique, de même que Pandoc qui est intégré à Quarto). VScode permet d’encapsuler également des chuncks de R (si R est chargé sur la machine avec les packages correspondants)

Le package sessioninfo de R permet de montrer comment on peut documenter automatiquement le code utilisé pour produire une figure à partir d’un jeu de données par exemple. La reproductibilité du code est un enjeu essentiel et connexe à l’accès aux données.

How to avoid predatory open access publishers

journal hijacking

figures

software used for this presentation

Références